Social Networks Week 3 NPTEL Assignment Answers 2025

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✅ Subject: Social Networks
📅 Week: 3
🎯 Session: NPTEL 2025 July-October
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NPTEL Social Networks Week 3 Assignment Answers 2025

1. According to Granovetter’s weak tie theory, which situation in this network is most likely to bring new information (like a job opportunity) to Alice?

• Alice’s close colleague in the same team shares a tip
• Alice learns of a job opening from a college acquaintance in another department
• Alice reads about the job in an internal memo posted by HR
• Alice’s mentor (her team leader) informs her directly

Answer : See Answers

2. In the company network, an edge between two employees has high embeddedness. What does this imply about their relationship?

• They have many mutual friends, so they trust each other and can enforce norms
• They are the only connection between their teams, acting as a bridge
• They share no common contacts (neighborhood overlap 0)
• They have completely different roles and no trust

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3. Alice acts as a liaison between the marketing and engineering teams, which are otherwise not directly connected. What network concept describes Alice’s advantage in this position?

• Clique formation
• Community detection
• Structural hole (brokerage)
• Triadic closure

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4. In this organizational network, an edge that is the only path connecting two distinct groups of employees (with no alternate route) is called a:

• Strong tie
• Local bridge
• Cluster edge
• Embedded tie

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5. In this context, which of the following statements about weak ties (Alice’s acquaintances) are correct?

• They tend to be bridges between groups and are crucial for information flow.
• They usually form redundant paths within a tightly knit team.
• They provide access to novel information from outside Alice’s team.
• They create high clustering (closed triads) in Alice’s local network.

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6. A friendship triad where each person is friends with the other two is called a:

• Closed triad (triangle)
• Structural hole
• Local bridge
• Open triad

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7. The local clustering coefficient of a student’s node measures:

• How likely the student is to start a rumor
• The proportion of the student’s friends who are also mutual friends with each other
• The number of weak ties the student has
• The number of communities the student belongs to

Answer : See Answers

8. If a student Dave has 4 friends, and among those friends there are 2 friendships (connections) between them, what is Dave’s local clustering coefficient? (Recall it is 2(# of realized friend-friend links)/(k(k-1)) for k friends.)

• 1/6
• 1/3
• 1/2
• 1

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9. The neighbourhood overlap of an edge between two students X and Y is defined as the fraction of their friends that they have in common. If X and Y share no mutual friends, their neighborhood overlap is 0, and that edge is a:

• Local bridge
• Closed triad
• Strong tie
• Embedded tie

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10. If Student Y shares 2 mutual friends with Student Z, and Y has total degree 5 (including Z) and Z has total degree 4 (including Y), the neighbourhood overlap is. Which choice best describes this overlap?

• 1/2
• 1/6
• 1/4
• 2/5

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11. An employee who connects many colleagues across different departments is likely to have increased:

• Social capital by bridging structural holes
• Network constraint and isolation
• Clustering coefficient in their local network
• Closed-loop redundancy

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12. In the Girvan–Newman community detection method, what is removed first to reveal communities?

• Nodes with highest degree
• Edges with highest betweenness centrality
• Random edges until clusters form
• Edges within dense subgroups

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13. The Girvan–Newman algorithm produces a hierarchy of communities in the form of a:

• Single cluster
• Dendrogram
• Flat partition
• Matrix of distances

Answer : See Answers

14. If Alice is a broker between two communities, what risk does she face according to social network theory?

• Increased time/energy to maintain ties (trade-off)
• Automatic promotion to a managerial position
• Losing all her intra-community ties
• Having a zero clustering coefficient

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15. Using the Girvan–Newman algorithm on a network with 20 employees, which approach does it use to determine community splits?

• Checking all possible divisions (brute force)
• Removing the lowest-weight edges first
• Iteratively removing edges with highest between-group communication
• Merging individuals into growing clusters until modularity peaks

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16. In the mobile phone network, if two users share a large number of common contacts (high neighbourhood overlap), what does Granovetter’s hypothesis predict about their call frequency?

• They will have a very low call frequency.
• They will likely have a high call frequency.
• Neighborhood overlap has no relation to call frequency.
• They will only communicate through intermediaries.

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17. Empirical findings from the mobile data suggest that edges with high weight (many calls) tend to have:

• High overlap (many mutual contacts)
• Zero overlap (no mutual contacts)
• Always be local bridges
• Be randomly distributed regardless of overlap

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18. In the call network, what kind of tie (based on overlap) is expected to connect two loosely connected clusters of individuals?

• A strong tie with high overlap
• A weak tie with near-zero overlap
• A repeated strong triadic tie
• A triadic closure edge

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19. Researchers found that confirming Granovetter’s theory in mobile data indicates which of the following about weak ties in this network?

• Weak ties were associated with high embeddedness.
• Weak ties tended to span between different clusters.
• Strong ties were never present.
• Weak ties had no role in information diffusion.

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20. If two city residents have an overlap ratio Oij=0.5O_ij=0.5 in their call network, which statement is true?

• They share all their contacts in common.
• They have half of their respective contacts in common (suggesting a fairly strong tie).
• They share no contacts in common.
• They do not communicate by phone.

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21. A brute-force community detection method:

• Iteratively removes edges by centrality.
• Tries every possible division of nodes into groups.
• Merges nodes based on degree.
• Uses edge overlap metrics only.

Answer : See Answers

22. The main drawback of brute-force methods compared to Girvan–Newman is:

• They cannot find the optimal solution.
• They run too quickly for large networks.
• They are computationally expensive (exponential time).
• They ignore edge weights.

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23. Girvan–Newman diff ers from brute-force in that it:

• Seeks communities by maximizing the local clustering coefficient.
• Recursively removes likely inter-community edges.
• Randomly assigns nodes to communities.
• Requires prior knowledge of the number of communities.

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24. In a small test network, both brute-force and Girvan–Newman find two communities of equal size. What advantage might Girvan–Newman have?

• It guaranteed the globally best partition.
• It is easier to explain by edge betweenness concept.
• It provides a clear hierarchy (dendrogram).
• It avoids calculating any centrality measures.

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25. Which statement is true about these two community detection approaches?

• Brute-force always yields fewer communities than Girvan–Newman.
• Girvan–Newman cannot handle weighted networks.
• Brute-force exhaustively finds the best split by any criterion (e.g., intra/inter edge ratio).
• Girvan–Newman is also brute-force in computing betweenness.

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26. A local bridge in this network is an edge whose endpoints have:

• High neighborhood overlap (many mutual friends).
• No mutual friends (neighborhood overlap 0).
• Maximum betweenness centrality.
• Been reinforced by multiple interactions.

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27. In terms of rumor propagation, edges with high embeddedness (many mutual neighbors) tend to:

• Quickly spread rumors to new parts of the network.
• Keep the rumor circulating within a local clique.
• Stop the rumor entirely.
• Always become local bridges.

Answer :

28. Which statement about rumors and weak ties is supported by network theory?

• Rumors spread faster along edges with many mutual friends.
• Bridges (weak ties) help the rumor jump between cliques.
• Only strong ties carry rumors in a dense network.
• Rumors cannot cross a local bridge.

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29. If student X has a friendship that is a local bridge to another cluster, X is likely:

• Highly embedded in their own clique and also well-connected to the other clique.
• Having no influence on rumor spread.
• The sole connection point for the rumor to reach the other cluster.
• Part of a complete triad with the other cluster.

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30. When a rumour starts in a dense clique, which tie is most critical for spreading it outside the clique?

• Any strong tie within the clique.
• Weak tie that is a local bridge to another clique.
• The tie with the highest clustering coefficient.
• A randomly chosen tie.

Answer : See Answers